The present invention is intended for use primarily with radio receivers operating in a high-signal-density environment. A Bragg Cell receiver is one type of receiver providing a wideband input and a signal handling capability sufficient to process a multitude of different signal types including radar and communication signals.
The parallel processing of a large number of such channelized signals on a real-time basis often exceeds the capabilities of conventional receivers. In general post detection processing electronics has not kept pace with developments in optical receivers. However, there are some things that can be done to reduce the demands on the signal processor. By limiting the final stages of receiver preprocessing to those channels containing signal information, processing speed and throughput are significantly improved. Such techniques significantly reduce the data rate output of a channelized receiver since the inactive channels can be removed prior to processing. In order to select the active channels from the total number, a noise threshold has to be defined either directly or indirectly and, in such a way to maintain a high probability of capturing the information in the active channels. In order to determine a noise threshold level (which is also called a constant false alarm rate level or simply a CFAR level), there are several common techniques. One method involves performing an FFT (fast Fourier Transform) on the guardbands of a signal. In the frequency domain, these guardbands lie on either side of the peak signal, and from these the noise level can be extracted. Another way is the rank select threshold method. Finally, should noise display a spectrum resembling a Gaussian distribution (as it often does), statistical techniques for determining noise can be employed.
There are trade-offs to be made in each of these techniques. For a system with a large number of channels, the guardband and rank select threshold methods prove to be complicated to implement since each frequency path requires its own rather complicated circuitry. Statistical methods present problems in real-time applications since the algorithms they utilize are complicated and time consuming.
In view of the foregoing, a principle object of the present invention is the provision of a data reduction processor that uses the total signal level in all incoming channels to determine the number of channels above and below a noise threshold level.
A further object of this invention is the provision of an adaptive noise threshold estimator that allows for continuously changing noise threshold levels to follow changing signal and noise levels in the incoming channels.
Still another object is the provision of a very stable and accurate method of estimating the wideband noise level which changes as the noise in the environment changes.